2016–2022 · Senior data analyst & leadership team
Building the data department
From one sentence to the company's full operational-intelligence function.
Built the data department from scratch and joined the leadership team. The original mandate was one sentence: "get the right product to the right store at the right time, every time", and I grew it into the company's full operational-intelligence and operations function.
Four systems, each one a class-solver rather than a one-off: a just-in-time replenishment model, a full cost-and-pricing model, a warehouse management system, and a nursery inventory system. Built hands-on in Excel and SQL, iterated for years across changing product lines, customers, and seasonality.
100,000+ forecasts a week across 1,000+ stores and 2,000+ perishable SKUs. One retailer went 17th to 2nd in national grossing rank in a single year after ceding inventory control to the model, with lifts of 20% or more typical.
"Get the right product to the right store at the right time, every time."
The entire job description. One letter-sized page, one sentence.
Illustrative bars, real ranks. Typical lift when stores ceded control: 20% or more.
built from scratch
Replenishment model
100,000+ forecasts a week. 17th to 2nd in a single year.
Built the just-in-time replenishment model from scratch in Excel, then migrated it to SQL once it outgrew the spreadsheet. It translates a 14-day SKU-by-store sell-through forecast into specific shipment quantities, accounting for supply constraints, store-level trends, and minimum economic order quantities. Iterated for five-plus years across changing product lines, customers, and seasonality. Award-winning; proprietary, so no live demo. That's the honest answer.
100,000+ unique forecasts per week, $100M+/yr of product movement on daily recommendations.
Costing & pricing model
Full cost build across 2,000+ SKUs.
A full cost build across 2,000+ SKUs: direct labour, materials, and direct and indirect overhead, allocated down to the unit. Sales used it to steer customers toward margin, pricing from a defensible cost floor instead of a gut feel. The same relational thinking that powered replenishment, pointed at the P&L.
direct labour, materials, direct + indirect overhead: every line traceable to a margin.
Sales priced from the cost floor, not a gut feel.
Warehouse management system
One spreadsheet on a thumb drive, replaced. 20M+ units tracked.
Inventory ran on a single spreadsheet on a thumb drive. I replaced it with a full PO, receiving, inventory, and transfer system tied directly to production, tracking 20M+ units. It drew down aging stock and cut production stoppages: the operational floor under everything the forecasts assumed.
- One spreadsheet on a thumb drive
- No live receiving or transfers
- Aging stock, invisible
- Production stoppages
- PO, receiving, inventory, transfers
- Tied to production, 20M+ units
- Aging stock drawn down
- Stoppages cut
A real system where there had been a file, tracking 20M+ units against production.
Nursery inventory system
600 acres, 500+ varieties, grow times up to 5 years.
Managed 600 acres and 500+ varieties with grow times stretching up to five years, optimizing what to grow as a plant's value shifts by age and stage. A forecasting problem in a different shape: the inventory is alive, the lead time is measured in seasons, and the wrong call compounds for years.
500+ varieties, optimized by age and stage: value shifts as a plant matures.
The inventory is alive; the wrong call compounds for years.